- Foreword
- Preface
- Chapter 1 Fundamental Considerations in Business Forecasting
- 1.1 Getting Real about Uncertainty
- 1.2 What Demand Planners Can Learn from the Stock Market
- 1.3 Toward a More Precise Definition of Forecastability
- 1.4 Forecastablity: A New Method for Benchmarking and Driving Improvement
- 1.5 Forecast Errors and Their Avoidability
- 1.6 The Perils of Benchmarking
- 1.7 Can We Obtain Valid Benchmarks from Published Surveys of Forecast Accuracy?
- 1.8 Defining “Demand” for Demand Forecasting
- 1.9 Using Forecasting to Steer the Business: Six Principles
- 1.10 The Beauty of Forecasting
- Chapter 2 Methods of Statistical Forecasting
- 2.1 Confessions of a Pragmatic Forecaster
- 2.2 New Evidence on the Value of Combining Forecasts
- 2.3 How to Forecast Data Containing Outliers
- 2.4 Selecting Your Statistical Forecasting Level
- 2.5 When Is a Flat-line Forecast Appropriate?
- 2.6 Forecasting by Time Compression
- 2.7 Data Mining for Forecasting: An Introduction
- 2.8 Process and Methods for Data Mining for Forecasting
- 2.9 Worst-Case Scenarios in Forecasting: How Bad Can Things Get?
- 2.10 Good Patterns, Bad Patterns
- Chapter 3 Forecasting Performance Evaluation and Reporting
- 3.1 Dos and Don’ts of Forecast Accuracy Measurement: A Tutorial
- 3.2 How to Track Forecast Accuracy to Guide Forecast Process Improvement
- 3.3 A “Softer” Approach to the Measurement of Forecast Accuracy
- 3.4 Measuring Forecast Accuracy
- 3.5 Should We Define Forecast Error as e = F – – A or e = A – – F?
- 3.6 Percentage Error: What Denominator?
- 3.7 Percentage Errors Can Ruin Your Day
- 3.8 Another Look at Forecast-Accuracy Metrics for Intermittent Demand
- 3.9 Advantages of the MAD/Mean Ratio over the MAPE
- 3.10 Use Scaled Errors Instead of Percentage Errors in Forecast Evaluations
- 3.11 An Expanded Prediction-Realization Diagram for Assessing Forecast Errors
- 3.12 Forecast Error Measures: Critical Review and Practical Recommendations
- 3.13 Measuring the Quality of Intermittent Demand Forecasts: It’s Worse than We’ve Thought!
- 3.14 Managing Forecasts by Exception
- 3.15 Using Process Behavior Charts to Improve Forecasting and Decision Making
- 3.16 Can Your Forecast Beat the Naïve Forecast?
- Chapter 4 Process and Politics of Business Forecasting
- 4.1 FVA: A Reality Check on Forecasting Practices
- 4.2 Where Should the Forecasting Function Reside?
- 4.3 Setting Forecasting Performance Objectives
- 4.4 Using Relative Error Metrics to Improve Forecast Quality in the Supply Chain
- 4.5 Why Should I Trust Your Forecasts?
- 4.6 High on Complexity, Low on Evidence: Are Advanced Forecasting Methods Always as Good as They Seem?
- 4.7 Should the Forecasting Process Eliminate Face-to-Face Meetings?
- 4.8 The Impact of Sales Forecast Game Playing on Supply Chains
- 4.9 Role of the Sales Force in Forecasting
- 4.10 Good and Bad Judgment in Forecasting: Lessons from Four Companies
- 4.11 Worst Practices in New Product Forecasting
- 4.12 Sales and Operations Planning in the Retail Industry
- 4.13 Sales and Operations Planning: Where Is It Going?
- About the Editors
- Index
- EULA
Business Forecasting
Practical Problems and Solutions
Edited by
Michael Gilliland
Len Tashman
Udo Sglavo
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